Most engineering orgs have solved for AI tool adoption already. What separates the ones getting real leverage from it is shared infrastructure, workflow automation, and guardrails that survive past the champions who first pushed for it.
At Docusign, that started with a peer-led model. Engineers across teams took on responsibility for embedding AI into daily workflows, documenting what actually worked, and surfacing the friction points that tooling alone couldn't fix. That foundation now spans across all 1,100+ of the company’s engineers.
Sagnik Nandy will walk through what came next, how Docusign's engineering org moved from individual AI adoption to a connected set of internal platforms spanning the SDLC – from coding to observability to agent orchestration – and the design decisions that made those platforms reusable for engineers and product teams rather than one-off tools.
He'll cover what worked, what didn't, and how the team distinguishes AI that's actually improving outcomes and developer productivity from AI that's just increasing usage.
Attendees will leave with a practical framework for designing AI platforms that scale past the pilot stage, and an open door to keep the conversation going with Docusign's engineering team after the session.
